In general, there is a trade-off between shorter exposure images and longer exposure images. A short exposure image typically is sharp because there is little motion blur, but such an image typically is noisy because the shorter exposure time typically results in underexposed pixels that produce image signals with low signal-to-noise-ratios. A long exposure image, on the other hand, typically is well exposed and therefore less noisy, but such an image typically is blurry because of motion that commonly occurs during the longer exposure period.
Some image enhancement approaches have been proposed for increasing the dynamic range (i.e., the ratio between the brightest and darkest parts of the scene) of an image by combining images of the same scene that were acquired at different exposure levels to produce a final image having a higher dynamic range than the constituent images. In these approaches, the pixel values in the final image typically are determined from a weighted average of the values of the corresponding pixels of the constituent images. In one dynamic range enhancement approach, an image that is characterized by high dynamic range, high signal-to-noise ratio, and reduced motion blur reportedly is produced by a recursive pixel-wise combination of pixel values obtained from a series of unfiltered multiple exposure images. In accordance with this approach, the pixel values of successive ones of the multiple exposure images are accumulated at each pixel location until either motion is detected between successive ones of the images or saturation of the image sensor is detected.
What are needed are improved systems and methods of generating images having increased sharpness and reduced noise.